Lecture 13 Other HCI Methods Brad Myers 05

Logistics l Exam information: l l l Thursday, Dec 17 at 8: 30 am, in Hamerschlag Hall room B 103 Monday, Dec. 21 at 2: 00 pm, in room Tepper 152 Anyone can go to either See: http: //www. cs. cmu. edu/~bam/uicourse/08763 fall 15/homework. html#7 Final date for late homeworks: TODAY Wednesday, December 16, 2015 Please fill out questionnaires: l l https: //cmu. smartevals. com or Tepper equivalent https: //www. surveymonkey. com/r/08763 fall 15 © 2015 - Brad Myers 2

Some Usability Methods l l l l Contextual Inquiry Contextual Analysis (Design) Paper Prototypes Low-Fidelity Prototypes Think-aloud protocols Heuristic Evaluation (6) Affinity diagrams (WAAD) Personas Wizard of Oz Task analysis (5) Questionnaires Cultural Probes Diary studies Card sorting (8) Body storming l l l l KLM and GOMS (Cog. Tool) “Speed Dating” Cognitive Walkthrough Cognitive Dimensions Video prototyping Expert interviews Surveys Interaction Relabeling Log analysis Focus groups Improvisation Use cases Scenarios A vs. B studies … © 2015 - Brad Myers 3

Other Methods l Other methods I have used: l l Taught to the HCI Masters students: l l Cognitive Walkthroughs, Cognitive Dimensions Cultural Probes & Diary Studies, Card Sorting, "Bodystorming", Keystroke Model & GOMS, "Speed Dating” Design methods vs. evaluation methods l l When are they useful? What kind of information is produced? © 2015 - Brad Myers 4

Design Methods l Use along side of CIs to find out more about your users, domains, etc. l l Many focused more on “feelings” and less on tasks and work l l l Also called generative methods – generate data & designs; also “formative” methods – help form the system Culture, aesthetics, etc. Others get at rare and intermittent occurrences Design methods: l l l Cultural Probes & Diary Studies Card Sorting Bodystorming © 2015 - Brad Myers 5

“Cultural Probes” l Bill Gaver, Tony Dunne, & E Pacenti, Design: Cultural Probes, ACM Interactions. vol. 6, no. 1, 1999, pp. 21 -29 l Goal – learn more about the users’ culture and feelings l l Give users a variety of recording devices (paper, maps, postcards, disposable cameras, audio-recorders) that they keep for a while Users are asked to record various aspects of their lives Examples: l l On postcards: “Please tell us a piece of advice or insight that has been important to you. ”; “Tell us about your favorite device. ” On a map: “Where would you like to go, but can’t” On a camera: “Please take pictures of: Your home; Something desirable; Something boring; whatever you want to show us” Looking for “Inspiration, not Information” l l capture general attitudes and social trends Beliefs and desires, aesthetic preferences, and cultural concerns Game-like & fun, but also respectful & interactive 6 © 2015 - Brad Myers Video (6: 23)

Diary Studies l l A variation on Cultural Probes Give users a diary and ask them to write about relevant events l l l E. g. , each time they have a problem with the system E. g. , whenever a rare event happens, write about aspects of it Good for rare events that users might not remembers the details of afterwards l Must happen when users can take the time to write down © 2015 - Brad Myers 7

Card Sorting l l Write important concepts on cards Get users to help organize them Hartson-Pyla text says same as Affinity Diagrams, but not necessarily Can find out: l l l What concepts go together? Groupings? What is a reasonable hierarchy? What would be better names for items? For groups? Video (1: 40) © 2015 - Brad Myers 8

“Bodystorming” l l l Marion Buchenau and Jane Fulton Suri. 2000. "Experience prototyping. " In Proceedings of the 3 rd conference on Designing interactive systems: processes, practices, methods, and techniques (DIS '00), pp. 424 -433. ACM DL PDF Term coined by Interval Research ~ for physically-situated brainstorming Designers pretend to be users, and act out the usage experience l l Example: buying a ticket at a kiosk l l In context, with as much fidelity as possible Discover constraints of the context Play different roles in a collaborative situation Now with gloves on, collaborating with another, etc. Example: radio for use in shower, close eyes © 2015 - Brad Myers 9

Example from our paper l l Kursat Ozenc, Miso Kim, John Zimmerman, Stephen Oney, and Brad Myers. "How to Support Designers in Getting Hold of the Immaterial Material of Software". Proceedings CHI'2010: Human Factors in Computing Systems. Atlanta, GA, April 10 -15, 2010. pp. 2513 -2522. local pdf The Radio team provides a good example of gesture through embodiment. In the process of designing the controls, they lay down on the floor, simulating the experience of lying in bed. From this position they sketched different interactions with their body, in one instance conceiving of a control that operates by continuously flipping the bedspread, and in another creating an expression that involved using both hands to wrap a pillow around the ears to communicate a desire for volume change. In all cases, these actions focused on how users might express their intentions to the system. © 2015 - Brad Myers 10

Evaluation Methods l l Use along side or instead of user testing & heuristic analyses Also called “summative” methods l l Get at different kinds of information l l To assess or compare the level of usability that has been achieved by the design Maximum expert performance How much learning is required? What concepts are needed? Evaluation Methods: l l Human Performance Modeling: KLM & GOMS “Speed Dating” Cognitive Walkthroughs Cognitive Dimensions © 2015 - Brad Myers 11

Human Performance Modeling l l l John, B. E. (2003) "Information processing and skilled behavior. " Chapter 4 In J. M. Carroll, (Ed. ), Toward a multidisciplinary science of human computer interaction. Morgan Kaufman. pp. 55 -101. Local CMU-only copy Hartson & Pyla, section 1. 6. 5 Goal: Compute measures of human performance without needing to do user tests Use a “model” of how people work, that has been validated to be reasonably accurate, given certain assumptions Works well for low-level, expert tasks l l l “How long will it take to enter this sequence of commands? ” Errors (both novice and skilled) Research on higher-level, problem solving tasks l Visual search, figure out how to do things, etc. © 2015 - Brad Myers 12

Wouldn’t it be great… l l Just point Mr. Bubblehead (the Model Human Processor) at a system, automatically generate performance measures, in context, AND see what’s inside its “mind” and “heart”? Better yet, point Mr. Bubblehead at design ideas (systems that haven’t been built yet) Fast, cheap, easy to interpret Quantitative measures to help persuade © 2015 - Brad Myers 13

The simplest model: the Keystroke-Level Model (KLM) l l Card. Moran & Newell, 1980, 1983 (CMN) l Pre-defined level of detail: K (keystroke), P (point with mouse), H (home between devices), M (mental operator), R (system response time) l Procedure for constructing a sequence of operators that perform a task l Heuristics for placing mental operators Input: l A suite of benchmark tasks that are important to your design or evaluation l A specification of the proposed system Output: l A prediction of the time it would take a skilled user to perform the benchmark tasks on the proposed system l Accurate to within about 20% of observed performance Appropriate for skilled performance, without problem solving © 2015 - Brad Myers 15

GOMS models l Goals, Operators, Methods, and Selection rules (GOMS) l l l Also originally from Card, Moran, and Newell Significant advances by Bonnie John in HCII and others Multiple strategies (“methods”) possible to do an operation (to reach a “goal”) (e. g. , delete a character) l l Each strategy uses a variety of “operators” “Selection rules” to pick which method l l E. g. , use backspace when previous character, use arrow keys when a few characters away, but use mouse when far away Write these in a special language (e. g. , ACT-R, SOAR) and system predicts how long tasks will take. 16 © 2015 - Brad Myers

Cog. Tool l Bonnie John’s tool to help with Cognitive Modeling http: //cogtool. hcii. cs. cmu. edu/ Mock-up an interface in a storyboard l l Use interactive widgets on a blank canvas l l States & transitions between those states Useful as a prototyping tool Outputs performance predictions © 2015 - Brad Myers 17

Cog. Tool produces predictions © 2015 - Brad Myers 18

Cog. Tool produces predictions through demonstrating tasks on a storyboard 1. Mock-up design in

Speed Dating l l Invented by CMU Ph. D students & faculty; now widely used Scott Davidoff, Min Kyung Lee, Anind K. Dey, and John Zimmerman. 2007. Rapidly exploring application design through speed dating. In Proceedings of the 9 th international conference on Ubiquitous computing (Ubi. Comp '07), Springer-Verlag, Berlin, Heidelberg, 429 -446. pdf l l l “Low-cost, rapid comparison of design opportunities and situated applications by creating structured, bounded, serial engagements. ” Usually used with sketches & storyboards of various designs that users can react to l l l (Thanks to Prof. Zimmerman for some of these slides) “Highly-disposable creations to support user enactments” Users discuss advantages and disadvantages of different designs/approaches Especially for when no existing product to evaluate l “Field work in the future” © 2015 - Brad Myers 20

Designer’s hunches l Leverage people’s familiarity with their current experiences in order to: l l infer how they might react to new products uncover desires they cannot expressed because they cannot imagine the future understand social boundaries the challenge is to connect them with their past experience Insert new step! © 2015 - Brad Myers 21

Really Two Methods l validation of needs l user enactments l (like bodystorming for

Example: 22 “Smart Home” scenarios © 2015 - Brad Myers 23

Users pick some that resonate © 2015 - Brad Myers 24

Another Example l l l From an M-HCI 2010 report Each sheet has one

Cognitive Walkthroughs l l Clayton Lewis and John Rieman, "4. 1. Cognitive Walkthroughs", in Task-Centered User Interface Design; A Practical Introduction (on-line book), 1994. html Cognitive Walkthroughs: Simulates user problem solving process l l For addressing ease of exploration Requires specific tasks Expert analysis Determine what knowledge the user would have to take each step of the task Ask questions at each step 1. Will users be trying to produce whatever effect the action has? 2. Will users see the control (button, menu, switch, etc. ) for the action? 3. Once users find the control, will they recognize that it produces the effect they want? 4. After the action is taken, will users understand the feedback they get, so they can go on to the next action with confidence? 26 l © 2015 - Brad Myers

Cognitive Dimensions l T. R. G. Green and M. Petre. Usability analysis of visual programming environments: A ‘cognitive dimensions’ framework. Journal of Visual Languages and Computing, 7: 131— 174, 1996. pdf See also: http: //www. cl. cam. ac. uk/~afb 21/Cognitive. Dimensions/ l 14 heuristics for evaluating usability of programming systems l 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. Abstraction gradient Closeness of mapping Consistency Diffuseness / terseness Error-proneness Hard mental operations Hidden dependencies Juxtaposability Premature commitment Progressive evaluation Role-expressiveness Secondary notation and escape from formalism Viscosity © 2015 - Brad Myers Visibility 27

#2: Closeness of mapping l l l Closeness of representation to domain How much problem solving does the user need to do to map task into the interface “Programming is the process of transforming a mental plan into one that is compatible with the computer. ” — Jean-Michel Hoc © 2015 - Brad Myers 28

No closeness-of-mapping class Hello. World. App { public static void main(String[] args) { System. out. println("Hello World!"); } } l l 3 kinds of parentheses and 9 special words! Compared to click and type: “Hello World!” in Power. Point © 2015 - Brad Myers 29

#7 Hidden Dependencies l l l Relationship between two components where the dependency is not fully visible E. g. , html links -> no back links IDEs may (or may not) help with finding uses of a variable, e. g. , to change it Formulas are hidden in spreadsheets, and dependencies on cells is doubly hidden Dataflow is hidden in regular languages, and control flow is hidden in dataflow languages © 2015 - Brad Myers 30

#9 Premature commitment l l Constraints on the order of doing things force the user to make a decision before the proper information is available. In C, the need to have procedures in a particular order in the file Phone menus require you to pick a number before hearing all the options Alice requires that you know whether you are going to want a control structure before knowing what goes in it © 2015 - Brad Myers 31

#13 Viscosity l l Resistance to change, the cost of making small changes Low: editing text to change “if” to “for” High: same edit in Alice Repetition viscosity: when difficult due to need to do it a lot l E. g. , no search/replace for graphics (change all to be ) © 2015 - Brad Myers 32